Microsoft Uses Multi-AI System to Generate Synthetic Attack Logs for Detection Testing

Microsoft's Defender Security Research Team has published a method that uses AI to generate synthetic attack logs based on MITRE ATT&CK techniques, aiming to address the chronic shortage of real-world attack data for building detection rules. The system takes attack tactics, specific procedures, and context such as target OS as inputs, then produces structured logs containing process names, parent-child relationships, command lines, and event sequences. A multi-AI pipeline — where separate models handle generation, evaluation, and improvement in a feedback loop — outperformed single-model approaches, especially for complex multi-step attack scenarios. The research was published on May 12, 2026, and is positioned as a lab-testing aid rather than a replacement for ground-truth logs captured from actual attack reproductions. Microsoft notes that synthetic logs cannot confirm real-world attack reproducibility but can meaningfully accelerate detection engineering where real data is scarce, sensitive, or costly to collect.